class_docstr: Randomly apply solarization transform to an image.
  This was used in BYOL - https://arxiv.org/abs/2006.07733
docstr: Args:
      p (float): Probability of applying the transform
docstr_tok: ["Args",":","p","(","float",")",":","Probability","of","applying","the","transform"]
code: def __init__(self, prob: float):
      """
      Args:
          p (float): Probability of applying the transform
      """
      self.p = prob
      transforms = [RandomSolarizeTransform()]
      self.transform = pth_transforms.RandomApply(transforms, self.p)
      logging.info(
          f"ImgPilRandomSolarize with prob {self.p} and {transforms}"
      )
  
file_path: vissl/vissl/data/ssl_transforms/img_pil_random_solarize.py
imports: import logging
  from typing import Any, Dict
  import torchvision.transforms
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
  from vissl.data.ssl_transforms.pil_photometric_transforms_lib import RandomSolarizeTransform
label_desc: Use image node_id 1 to create a new ImgPilRandomSolarize object from inherited base classes: ClassyTransform with example: obj = ImgPilRandomSolarize(prob)